OpenRaiser/Intern-Atlas huggingface dataset:
Independent Component Analysis for Filtering Airwaves in Seabed Logging Application
Venue: arXiv cs.OH 2013
Year: 2013

Marine controlled source electromagnetic (CSEM) sensing method used for the detection of hydrocarbons based reservoirs in seabed logging application does not perform well due to the presence of the airwaves (or sea-surface). These airwaves interfere with the signal that comes from the subsurface seafloor and also tend to dominate in the receiver response at larger offsets. The task is to identify these air waves and the way they interact, and to filter them out. In this paper, a popular method for counteracting with the above stated problem scenario is Independent Component Analysis (ICA). Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional or multivariate dataset into its constituent components (sources) that are statistically as independent from each other as possible. ICA-type de-convolution algorithm that is FASTICA is considered for mixed signals de-convolution and considered convenient depending upon the nature of the source and noise model. The results from the FASTICA algorithm are shown and evaluated. In this paper, we present the FASTICA algorithm for the seabed logging application.
Integrating Space, Time, Version and Scale Using Alexandrov Topologies
Venue: arXiv cs.DB 2013
Year: 2013

This article introduces a novel approach to spatial database design. Instead of extending the canonical Solid-Face-Edge-Vertex schema by, say, "hypersolids" these classes are generalised to a common type SpatialEntity, and the individual BoundedBy relations between two consecutive classes are generalised to one BoundedBy relation on SpatialEntity instances. Then the pair (SpatialEntity, BoundedBy) is a so-called incidence graph. The novelty about this approach uses the observation that an incidence graph represents a topological space of SpatialEntity instances because the BoundedBy-relation defines a so-called Alexandrov topology for them turning them into a topological space. So spatial data becomes part of mathematical topology and topology can be immediately applied to spatial data. For example, continuous functions between two instances of spatial data allow the consistent modelling of generalisation. Further, it is also possible to establish a formal topological definition of spatial data dimension, and every topological data model of arbitrary dimension gets a simple uniform data model. This model covers space-time, and the version history of a spatial model can be represented by an Alexandrov topology, too. By integrating space, time, version, and scale into one single schema, topological queries across those aspects are enabled through topological constructions. In fact, the topological constructions cover a relationally complete query language for spaces and can be redefined to operate accordingly on their graph representations. With these observations a relational database schema for a spatial data model of dimension 6 and more is developed. The schema seamlessly integrates 4D space-time, levels of detail and version history, and it can be easily expanded to also contain non-spatial information or be linked to other data sources.
Low-Complexity Constrained Constant Modulus SG-based Beamforming Algorithms with Variable Step Size
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, two low-complexity adaptive step size algorithms are investigated for blind adaptive beamforming. Both of them are used in a stochastic gradient (SG) algorithm, which employs the constrained constant modulus (CCM) criterion as the design approach. A brief analysis is given for illustrating their properties. Simulations are performed to compare the performances of the novel algorithms with other well-known methods. Results indicate that the proposed algorithms achieve superior performance, better convergence behavior and lower computational complexity in both stationary and non-stationary environments.
Gaussian Mixture Model for Handwritten Script Identification
Venue: arXiv cs.CV 2013
Year: 2013

This paper presents a Gaussian Mixture Model (GMM) to identify the script of handwritten words of Roman, Devanagari, Kannada and Telugu scripts. It emphasizes the significance of directional energies for identification of script of the word. It is robust to varied image sizes and different styles of writing. A GMM is modeled using a set of six novel features derived from directional energy distributions of the underlying image. The standard deviation of directional energy distributions are computed by decomposing an image matrix into right and left diagonals. Furthermore, deviation of horizontal and vertical distributions of energies is also built-in to GMM. A dataset of 400 images out of 800 (200 of each script) are used for training GMM and the remaining is for testing. An exhaustive experimentation is carried out at bi-script, tri-script and multi-script level and achieved script identification accuracies in percentage as 98.7, 98.16 and 96.91 respectively.
A Tutorial on the Optimization of Amplify-and-Forward MIMO Relay Systems
Venue: arXiv cs.IT 2013
Year: 2013

The remarkable promise of multiple-input multiple-output (MIMO) wireless channels has motivated an intense research activity to characterize the theoretical and practical issues associated with the design of transmit (source) and receive (destination) processing matrices under different operating conditions. This activity was primarily focused on point-to-point (single-hop) communications but more recently there has been an extensive work on two-hop or multi-hop settings in which single or multiple relays are used to deliver the information from the source to the destination. The aim of this tutorial is to provide an up-to-date overview of the fundamental results and practical implementation issues of designing amplify-and-forward MIMO relay systems.
Power Allocation in Two-Hop Amplify-and-Forward MIMO Relay Systems with QoS requirements
Venue: arXiv cs.IT 2013
Year: 2013

The problem of minimizing the total power consumption while satisfying different quality-of-service (QoS) requirements in a two-hop multiple-input multiple-output network with a single non-regenerative relay is considered. As shown by Y. Rong in [1], the optimal processing matrices for both linear and non-linear transceiver architectures lead to the diagonalization of the source-relay-destination channel so that the power minimization problem reduces to properly allocating the available power over the established links. Unfortunately, finding the solution of this problem is numerically difficult as it is not in a convex form. To overcome this difficulty, existing solutions rely on the computation of upper- and lower-bounds that are hard to obtain or require the relaxation of the QoS constraints. In this work, a novel approach is devised for both linear and non-linear transceiver architectures, which allows to closely approximate the solutions of the non-convex power allocation problems with those of convex ones easy to compute in closed-form by means of multi-step procedures of reduced complexity. Computer simulations are used to assess the performance of the proposed approach and to make comparisons with alternatives.
Gaussian Processes for Nonlinear Signal Processing
Venue: arXiv cs.LG 2013
Year: 2013

Gaussian processes (GPs) are versatile tools that have been successfully employed to solve nonlinear estimation problems in machine learning, but that are rarely used in signal processing. In this tutorial, we present GPs for regression as a natural nonlinear extension to optimal Wiener filtering. After establishing their basic formulation, we discuss several important aspects and extensions, including recursive and adaptive algorithms for dealing with non-stationarity, low-complexity solutions, non-Gaussian noise models and classification scenarios. Furthermore, we provide a selection of relevant applications to wireless digital communications.
A Note on Connected Dominating Set in Graphs Without Long Paths And Cycles
Venue: arXiv cs.DM 2013
Year: 2013

The ratio of the connected domination number, $γ_c$, and the domination number, $γ$, is strictly bounded from above by 3. It was shown by Zverovich that for every connected $(P_5,C_5)$-free graph, $γ_c = γ$. In this paper, we investigate the interdependence of $γ$ and $γ_c$ in the class of $(P_k,C_k)$-free graphs, for $k \ge 6$. We prove that for every connected $(P_6,C_6)$-free graph, $γ_c \le γ+ 1$ holds, and there is a family of $(P_6,C_6)$-free graphs with arbitrarily large values of $γ$ attaining this bound. Moreover, for every connected $(P_8,C_8)$-free graph, $γ_c / γ\le 2$, and there is a family of $(P_7,C_7)$-free graphs with arbitrarily large values of $γ$ attaining this bound. In the class of $(P_9,C_9)$-free graphs, the general bound $γ_c / γ\le 3$ is asymptotically sharp.
Quantum finite automata and linear context-free languages: a decidable problem
Venue: arXiv cs.FL 2013
Year: 2013

We consider the so-called measure once finite quantum automata model introduced by Moore and Crutchfield in 2000. We show that given a language recognized by such a device and a linear context-free language, it is recursively decidable whether or not they have a nonempty intersection. This extends a result of Blondel et al. which can be interpreted as solving the problem with the free monoid in place of the family of linear context-free languages.
Data Retrieval over DNS in SQL Injection Attacks
Venue: arXiv cs.CR 2013
Year: 2013

This paper describes an advanced SQL injection technique where DNS resolution process is exploited for retrieval of malicious SQL query results. Resulting DNS requests are intercepted by attackers themselves at the controlled remote name server extracting valuable data. Open source SQL injection tool sqlmap has been adjusted to automate this task. With modifications done, attackers are able to use this technique for fast and low profile data retrieval, especially in cases where other standard ones fail.
Robust Auxiliary Vector Filtering with Constrained Constant Modulus Design for Beamforming
Venue: arXiv cs.IT 2013
Year: 2013

This paper proposes an auxiliary vector filtering (AVF) algorithm based on a constrained constant modulus (CCM) design for robust adaptive beamforming. This scheme provides an efficient way to deal with filters with a large number of elements. The proposed beamformer decomposes the adaptive filter into a constrained (reference vector filters) and an unconstrained (auxiliary vector filters) components. The weight vector is iterated by subtracting the scaling auxiliary vector from the reference vector. The scalar factor and the auxiliary vector depend on each other and are jointly calculated according to the CCM criterion. The proposed robust AVF algorithm provides an iterative exchange of information between the scalar factor and the auxiliary vector and thus leads to a fast convergence and an improved steady-state performance over the existing techniques. Simulations are performed to show the performance and the robustness of the proposed scheme and algorithm in several scenarios.
Using Mathematica & Matlab for CAGD/CAD research and education
Venue: arXiv cs.CY 2013
Year: 2013

In CAGD/CAD research and education, users are involved with development of mathematical algorithms and followed by the analysis of the resultant algorithm. This process involves geometric display which can only be carried out with high end graphics display. There are many approaches practiced and one of the so-called easiest approaches is by using C/C++ programming language and OpenGL application program interface, API. There are practitioners uses C/C++ programming language to develop the algorithms and finally utilize AutoCAD for graphics display. On the other hand, high end CAD users manage to use Auto Lisp as their programming language in AutoCAD. Nevertheless, these traditional ways are definitely time consuming. This paper introduces an alternative method whereby the practitioners may maximize scientific computation programs, SCPs: Mathematica and MATLAB in the context of CAGD/CAD for research and education.
Material quality assessment of silk nanofibers based on swarm intelligence
Venue: arXiv cs.CV 2013
Year: 2013

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.
FindZebra: A search engine for rare diseases
Venue: arXiv cs.IR 2013
Year: 2013

Background: The web has become a primary information resource about illnesses and treatments for both medical and non-medical users. Standard web search is by far the most common interface for such information. It is therefore of interest to find out how well web search engines work for diagnostic queries and what factors contribute to successes and failures. Among diseases, rare (or orphan) diseases represent an especially challenging and thus interesting class to diagnose as each is rare, diverse in symptoms and usually has scattered resources associated with it. Methods: We use an evaluation approach for web search engines for rare disease diagnosis which includes 56 real life diagnostic cases, state-of-the-art evaluation measures, and curated information resources. In addition, we introduce FindZebra, a specialized (vertical) rare disease search engine. FindZebra is powered by open source search technology and uses curated freely available online medical information. Results: FindZebra outperforms Google Search in both default setup and customised to the resources used by FindZebra. We extend FindZebra with specialized functionalities exploiting medical ontological information and UMLS medical concepts to demonstrate different ways of displaying the retrieved results to medical experts. Conclusions: Our results indicate that a specialized search engine can improve the diagnostic quality without compromising the ease of use of the currently widely popular web search engines. The proposed evaluation approach can be valuable for future development and benchmarking. The FindZebra search engine is available at http://www.findzebra.com/.
Structural Results and Explicit Solution for Two-Player LQG Systems on a Finite Time Horizon
Venue: arXiv cs.SY 2013
Year: 2013

It is well-known that linear dynamical systems with Gaussian noise and quadratic cost (LQG) satisfy a separation principle. Finding the optimal controller amounts to solving separate dual problems; one for control and one for estimation. For the discrete-time finite-horizon case, each problem is a simple forward or backward recursion. In this paper, we consider a generalization of the LQG problem in which there are two controllers. Each controller is responsible for one of two system inputs, but has access to different subsets of the available measurements. Our paper has three main contributions. First, we prove a fundamental structural result: sufficient statistics for the controllers can be expressed as conditional means of the global state. Second, we give explicit state-space formulae for the optimal controller. These formulae are reminiscent of the classical LQG solution with dual forward and backward recursions, but with the important difference that they are intricately coupled. Lastly, we show how these recursions can be solved efficiently, with computational complexity comparable to that of the centralized problem.
Towards a Synergy-based Approach to Measuring Information Modification
Venue: arXiv cs.IT 2013
Year: 2013

Distributed computation in artificial life and complex systems is often described in terms of component operations on information: information storage, transfer and modification. Information modification remains poorly described however, with the popularly-understood examples of glider and particle collisions in cellular automata being only quantitatively identified to date using a heuristic (separable information) rather than a proper information-theoretic measure. We outline how a recently-introduced axiomatic framework for measuring information redundancy and synergy, called partial information decomposition, can be applied to a perspective of distributed computation in order to quantify component operations on information. Using this framework, we propose a new measure of information modification that captures the intuitive understanding of information modification events as those involving interactions between two or more information sources. We also consider how the local dynamics of information modification in space and time could be measured, and suggest a new axiom that redundancy measures would need to meet in order to make such local measurements. Finally, we evaluate the potential for existing redundancy measures to meet this localizability axiom.
Non-blocking Patricia Tries with Replace Operations
Venue: arXiv cs.DC 2013
Year: 2013

This paper presents a non-blocking Patricia trie implementation for an asynchronous shared-memory system using Compare&Swap. The trie implements a linearizable set and supports three update operations: insert adds an element, delete removes an element and replace replaces one element by another. The replace operation is interesting because it changes two different locations of tree atomically. If all update operations modify different parts of the trie, they run completely concurrently. The implementation also supports a wait-free find operation, which only reads shared memory and never changes the data structure. Empirically, we compare our algorithms to some existing set implementations.
Adaptive Low-rank Constrained Constant Modulus Beamforming Algorithms using Joint Iterative Optimization of Parameters
Venue: arXiv cs.IT 2013
Year: 2013

This paper proposes a robust reduced-rank scheme for adaptive beamforming based on joint iterative optimization (JIO) of adaptive filters. The scheme provides an efficient way to deal with filters with large number of elements. It consists of a bank of full-rank adaptive filters that forms a transformation matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. The transformation matrix projects the received vector onto a low-dimension vector, which is processed by the reduced-rank filter to estimate the desired signal. The expressions of the transformation matrix and the reduced-rank weight vector are derived according to the constrained constant modulus (CCM) criterion. Two novel low-complexity adaptive algorithms are devised for the implementation of the proposed scheme with respect to different constrained conditions. Simulations are performed to show superior performance of the proposed algorithms in comparison with the existing methods.
A Survey of Routing Techniques for Mobile Collaborative Virtual Environment Applications
Venue: arXiv cs.NI 2013
Year: 2013

Due to the rapidly increasing usage of personal mobile devices and the need of executing CVE applications in environments that have no previous network infrastructure, Mobile Collaborative Virtual Environments (MCVEs) systems will become ubiquitous in the future. In such systems, we enable users to act and interact in three dimensional world shared through their mobile devices in an ad-hoc network (MANET). A handful of interesting MCVE applications have been developed in a variety of domains, ranging from multiplayer games to virtual cities, virtual shopping malls, and various training simulations (i.e. military, emergency preparedness, Education, Medicine, etc.). The designers of such applications rely solely on network overhead, latency, limited bandwidth, and mobile device limitation. In this survey we present a number of ways to classify and analysis routing techniques that have been applied in Mobile Collaborative Environment Applications.
A Randomized Approach to the Capacity of Finite-State Channels
Venue: arXiv cs.IT 2013
Year: 2013

Inspired by the ideas from the field of stochastic approximation, we propose a randomized algorithm to compute the capacity of a finite-state channel with a Markovian input. When the mutual information rate of the channel is concave with respect to the chosen parameterization, we show that the proposed algorithm will almost surely converge to the capacity of the channel and derive the rate of convergence. We also discuss the convergence behavior of the algorithm without the concavity assumption.
Access vs. Bandwidth in Codes for Storage
Venue: arXiv cs.IT 2013
Year: 2013

Maximum distance separable (MDS) codes are widely used in storage systems to protect against disk (node) failures. A node is said to have capacity $l$ over some field $\mathbb{F}$, if it can store that amount of symbols of the field. An $(n,k,l)$ MDS code uses $n$ nodes of capacity $l$ to store $k$ information nodes. The MDS property guarantees the resiliency to any $n-k$ node failures. An \emph{optimal bandwidth} (resp. \emph{optimal access}) MDS code communicates (resp. accesses) the minimum amount of data during the repair process of a single failed node. It was shown that this amount equals a fraction of $1/(n-k)$ of data stored in each node. In previous optimal bandwidth constructions, $l$ scaled polynomially with $k$ in codes with asymptotic rate $<1$. Moreover, in constructions with a constant number of parities, i.e. rate approaches 1, $l$ is scaled exponentially w.r.t. $k$. In this paper, we focus on the later case of constant number of parities $n-k=r$, and ask the following question: Given the capacity of a node $l$ what is the largest number of information disks $k$ in an optimal bandwidth (resp. access) $(k+r,k,l)$ MDS code. We give an upper bound for the general case, and two tight bounds in the special cases of two important families of codes. Moreover, the bounds show that in some cases optimal-bandwidth code has larger $k$ than optimal-access code, and therefore these two measures are not equivalent.
Organization Mining Using Online Social Networks
Venue: arXiv cs.SI 2013
Year: 2013

Mature social networking services are one of the greatest assets of today's organizations. This valuable asset, however, can also be a threat to an organization's confidentiality. Members of social networking websites expose not only their personal information, but also details about the organizations for which they work. In this paper we analyze several commercial organizations by mining data which their employees have exposed on Facebook, LinkedIn, and other publicly available sources. Using a web crawler designed for this purpose, we extract a network of informal social relationships among employees of a given target organization. Our results, obtained using centrality analysis and Machine Learning techniques applied to the structure of the informal relationships network, show that it is possible to identify leadership roles within the organization solely by this means. It is also possible to gain valuable non-trivial insights on an organization's structure by clustering its social network and gathering publicly available information on the employees within each cluster. Organizations wanting to conceal their internal structure, identity of leaders, location and specialization of branches offices, etc., must enforce strict policies to control the use of social media by their employees.